DOI: 10.4018/IJTHI.2018070105
Copyright©2018,IGIGlobal.CopyingordistributinginprintorelectronicformswithoutwrittenpermissionofIGIGlobalisprohibited.
Exploring the Similarities Between
Users and Non-Users of Consumer
Mobile Internet Services:
Towards a Porosity Model of
Technology Acceptance
Stéphanie Gauttier, Université de Nantes, Nantes, France Claire Gauzente, Université de Nantes, Nantes, France
ABSTRACT Whilemobiletechnologieshavebecomepervasive,someconsumersremainreluctanttoaccept, adoptandusethem.Literaturetraditionallyopposesthenotionsof‘user’and‘non-user’butrecent developmentsshowtheboundarybetweenthesetwoconceptsisverythin.Theaimofthisarticleis toreviewtheoreticalframeworksthatareavailableforunderstandingsuchconsumerattitudesand behavioursandtoconfronttheoreticalanalysiswithin-depthsubjectiveinvestigationofanon-user, occasionaluserandheavyuser,facingasetofdifferentmobilemediaoffers.Theempiricalanalysis isconductedusingQ-method.Resultsdemonstratesimilaritiesamongusersandnon-userswhen consideringtheirattitudetowardsdifferenttechnologies,whichopensopportunitiesformarket consumertechnologiestoincreasetheirpenetrationrate. KEywoRdS
Media and Technology Adoption, Non-Use, Partial Use, Q-Method, Technology Use INTRodUCTIoN In2016,79%ofEuropeancitizensaccessedtheInternetatleastonceaweek.Andyet,45%of Europeancitizensdidn’tpurchasegoodsonline.41%didn’tusetheInternetonamobilehandheld devicein20161.Thismeansthatbusinessesmissasignificantpartofthepopulationwhenreleasing mobileInternetservices. Yet,researchonconsumeruseofmobileservicesfocusesontheusers,andnon-usersare consideredinoppositiontothem.Therealityofnon-useismuchmorenuanced,asnon-usersofa specifictechnologycanusesomeothertechnologiesormakepartialuseofatechnology.Thatmeans non-usecanbeunderstoodonlyinrelationtouse,notnecessarilyinoppositiontoit.Thelackoffocus onthesimilaritiesbetweennon-usersandusersandtheirmotivation(not)tousepreventsdesign servicesforwideraudiences.Therefore,thisstudylooksatsharedrepresentationsoftechnologies
betweendifferenttypesof(non)-users.Itfocusesonmobiletechnologiesandmobileservicesoffered toconsumers,suchasM-payment,augmentedreality,QR-codeandM-ticket. Thecontributionofthisresearchisthusthreefold.First,ittriestobridgethedivideinliterature betweenusersandnon-usersbyconsideringthepointofviewofthreedifferenttypesofmobile technologyusers(non-user,occasionaluser,heavyuser)onasetofdifferentmobileservicesprovided bybrandsorretailers.Fromamanagerialstandpoint,itallowspractitionerstounderstandhowpositive andnegativeattitudetowardsdifferentservicesareformed,sotheycanintegrateconsumerservices totheirbusinessmoreeffectively.Finally,itsuggeststhatQ-methodstudiescandocumenteffectively theviewpointofreluctantconsumersandunveiltowhatextentnon-useisactual,partial,arbitrary, paradoxical,andfarfromabinaryvariable. Thispaperisorganizedinfoursections.First,wereviewliteratureonuseandnon-use.Secondly, wepresentourresearchquestionandmethodology.Thirdly,wepresenttheresultsofthestudy.Finally, wediscussthoseresultsinrelationtoexistingliteratureandfutureresearch. RELATEd LITERATURE Theanalysisofuse(1)andnon-useliterature(2)revealsthatalthoughliteraturededicatedtousage andliteraturededicatedtonon-usageshouldhavemirror-likelogic,theunderlyingperspectivesare indeeddifferent.Whenitcomestoconsumeruseoftechnology,researchadoptstheprismof‘use’(3). Approachesconsideringnon-useofconsumertechnologyarerequiredtobeabletomarketconsumer servicesinamoreefficientway.Theseapproachesmustconsiderthesubjectiverepresentational spaceofuserstoexplaintheirperceptionandbehaviour.
Literature on Use: Focus on operational and Social Acceptation
AuserisdefinedintheISO/IECstandards2007and2011(Baumer,Ames,Burrell,Brubacker,& Dourish,2015)as‘anindividualorgroupwhousesasoftwareproducttoperformaspecificfunction’ andgets‘benefitsfromitsutilization’. Theusage-centredstudiescanbesplitintotwosub-categoriesidentifiedbyBrangier,Hammes-AdeléandBastien(2010):theoperationalacceptationononehandandthesocialacceptationonthe otherhand. Theoperationalacceptationoftechnologyderivesfromtheergonomicswheretheusability, ergonomiccriteriaandmodelofinteractionareattheheartoftechnologicalacceptance.However, beyondoperationalacceptancewhichisimportantfromadesignstandpoint,OrlikowskiandBaroudi (1991,p.7)pointedoutthatresearchersneedtounderstandsocialprocessesthatunderliethe introduction,creation,use,misuseandabandonofICT. Forthisreason,severaltheoreticalattemptsweremadeinordertoconceptualizetechnologyuse. OneofthemostprominentmodelsistheTAM–TechnologyAcceptanceModel,proposedbyDavis (1986,1989)andrefinedinsubsequentpublications.Thismodelexplainsintentiontouseandactual usebyattitudetowardtechnology,perceivedusefulnessandperceivedeaseofuse.Thismodelis verypopularandhasbeentestedinmanysettings.Critiquesandrefinementshavealsoemergedwith time(Legris,Ingham&Collerette,2003;Turner,Kitchenham,Brereton,Chareters&Budgen,2010; Brangieretal,op.cit.).Alternativeconceptualizationshavealsobeenproposed.Amongthemost fruitful,wecancitetheExpectation-ConfirmationTheory-ECT(Bhattacherjee,2001;Bhattacherjee &Premhumar,2004)derivedfromtheSatisfactionApproach(Oliver,1980),theTask-TechnoFit Model-TTF(Cane&McCarthy,2009;Goodhue&Thompson,1995),theStructurationistapproach (DeSanctis&Poole,1994;Orlikowski,1992),andtheCopingModelofUserAdaptation(Beaudry &Pinsonneau,2005,2010). TheseapproachesaddressdifferentstagesandaspectsofICTacceptanceanduse.TheECT modelsuggeststhatexpectationstowardthetechnologyatonepointintimeandthesatisfaction
derivedfromitsfirstuseexplainthedecisiontousetechnologyinthefuture.ContinuedICTuseis thenrelatedtoexpectationsandtheirconfirmationviasatisfactionandperceivedvalue(Dai,Hu,& Zhang,2014).TheTTFmodelholdsthatutilizationdependsonthetasktobeaccomplishedandthe technologicalcharacteristics.Whentaskrequirementsandtechnologycharacteristicsfit,utilization andsatisfactionaremoreliable.Fitassessmentdependsontheusecontext.Inthelongrun,the individuals’performanceinICTuseisalsomorelikely.Thestructurationistapproachpointsoutthat ITuse,mainlyinorganizations,challengestheoryandorganizationsasitinduceschanges.Adynamic andinteractionistviewisproposedandemphasizessocialinteractionsemergingfromITadoption anduse.TheCopingModelofUserAdaptationsuggeststhatemotionsconstituteasignificantpart ofICTacceptation,firstuseandcontinueduse.Differentemotionshavebeenstudied:enjoyment, pleasure,anxietyandplayfulness. Allinall,thesedifferentapproachesholdacommonviewthattechnologyacceptanceanduse issociallyconstructed,influencedbyutilizationcontext,andbyindividuals’emotionsandattitudes. Inlinewiththis,ITuseornon-usedoesnotmerelyappearasamatterofmeetingergonomicor technicalrequirements.Thesocialstanceatacceptingandusingtechnologyisalsoprevalentinthe non-usageliterature.
Non-Use Literature: Move Towards Understanding Voluntary Non-Use
Non-usershavelongbeenseenasindividualswhodonothaveaccesstotechnology.Non-usage approachesincludemanydigitaldividestudiessuchasRiceandKatz(2003)andrepresentadynamic streamofresearch(Brandtzæg,Heim,&Karahasanovic,2011;Cruz-Jesus,Oliveira,&Bacao,2012). Themostclassicalpredictorsofdigitalinequalitiesareincomeorsocio-economicstatusaswellas gender,age,education,andfamilystructure.Suchapproachesconsiderthatnon-usershavenoagency overtheiraccesstotechnologyandareinvoluntarynon-users.Andyet,othercategoriesofnon-users areemerging.Theycanbemappedoutas1)resisters,whoneverhadaccesstoatechnologyand neverwantedit;2)rejecters,whotriedatechnologybutgaveitupvoluntarily;3)expelled,whohad accessbutlostit;4)excluded,whohavenoaccesstotechnologybuthavenotchosenit(Wyatt,2003). Researchonnon-usefocusesonpracticesofnon-use(VanHouse,2015),butthemotivations behindnon-useareonlylittleunderstood.HCIlooksatnon-useasabarriertoadoption,whilenon-useisaformofusethatismeaningful,motivatedanddirected.VanHouse(2015)highlightsthere’sa lightofunderstandinginthemotivationsbehindnon-use,asmotivation-focusedresearchisfocusing onbehaviourchangegoals(Sleeper,Acquisti,Cranor,Kelley,Munson&Sadeh,2015),andothers lookatacost-advantagesrelationship(Selwyn2003,Baumeretal2015).Oneofthechallengesfaced byresearchonnon-useisthedifficultyfornon-userstoexplaintheirbehaviourbeyondbeing‘not interested’(VanHouse,2015;Lampe,Vitak,&Ellison,2013).Lampeetal(2013)declarethatthis answerisacoverformorecomplexconcerns.Often,non-usageislookedfromtheperspectiveof thetechnology,inauni-dimensionalway.Approachesallowingtocapturethecomplexrelationship ofnon-userstotechnologyarerequired.Thestatusofnon-userisnotabsolute.Rather,oneshould considerdevelopingacontinuumoftypesofinvolvementwithtechnologyconsideringthedynamic andmulti-dimensionalrelationshiponehaswithtechnology(Wyatt,2014).Forinstance,Neves,De Matos,Rente,andMartins(2015)proposeatypologywithresisters,rejecters,surrogateusers(using somebodyelse’sdevice),andpotentialconverts,whoareconsideringorreconsideringtechnology use.Beinganon-userisalsorelativetoaspecificpotentialorimagineduseoftechnology(Ems, 2015).Integratingusage-centeredliterature,andparticularlytheutilityconcept,opensalternative interpretationsofnon-use(Verdegem&Verhoest,2009).VerdegemandVerhoest(2009)developedthe ASAmodel,comprisingAccess,SkillsandAttitude,inordertoexplaintechnologyappropriationand thuse-inclusionorexclusion.ThisechoestheworkbySelwyn(2003,2006)whoalreadyunderlined thatthepatternsofnon-engagementintechnologyandmediavarybetweentechnologiesandfeature differenttypesofnon-users.Typically,Selwyndistinguishesthreereasonsfornon-usage:non-access
(lackofeconomic,culturalorcognitiveresources);technophobiaandideologicalrefusal.Resistance tonewmediadevelopmentscanalsobeexplainedbyacombinationofassemblageandaffecttheory (Thorén&Kitzmann,2015).ThestudybyThorénandKitzmannshowthatdigitaltechnologies formusiccanbeignoredbyindividualswhoseetheirmusicalentertainmentasanemotionaland experientialactivity. Otherrefinementsexist,forinstance,Jauréguiberry(2012)focusesmorepreciselyonvoluntary non-usagewherenon-useisnotnecessarilyabsolute,butpartial(certainusagesaresimplypaused) andsegmented(limitedtocertainperiodsofthedayforinstance).RibakandRosenthal(2015)show thatthistypeofresistance,whichtheycallmediaambivalence,isdirectedatonetechnologyandits personalmeaningandsocietalsignificanceevolvesovertime.Adichotomybetweenusersandnon-usersdoesn’thold,asindividualsarebothusersandnon-usersatthesametime.Rather,personal motivesforusingspecifictechnologieswhilstavoidingothersiskeytounderstandingbehaviours ofuseandnon-use.
Consumer Technology Usage: Mainly Approached Through the ‘Use’ Literature TheappearanceofnewtechnologiestriggerstheinterestofAcademicstoresearchtheirpotentials forconsumerservices.Forinstance,theuseofsmsadvertising(Gauzente,2010),augmentedreality (BulearcaandTamarjan,2010),orQR-codes(Okazaki,Navarro-Bailon,&Milna-Castillo,2012b) hasbeeninvestigated.Thisresearchismainlydescriptiveandcanbeclassifiedintothreecategories: 1. Studiesexplainingtheformationofusers’perceptionoftechnologyandtheirimpactonuse (Gauzente,2010,Okazaki,etal.,2012b); 2. Studiesexplainingattitudetowardsthetechnology,withresearchontheroleofdifferentvariables suchasubiquity(Okazaki,Molina&Hirose,2012a)orprivacy,trustandsatisfaction(Kim& Lim,2001)onattitudetowardsthetechnology; 3. Researchlookingattheimpactofconsumertechnologyexperienceonpurchase(Koivumäki, 2001),brandattitudeandhedonicsideofshopping(Bulearca&Tamarjan,2010). Thefocusofthisresearchisonusers.Modelsandapproachescomingfromthe‘use’literature isadoptedandadaptedtoconsumeruseoftechnology.Forinstance,thereisastreamofliterature lookingmorecloselyastohowtheTAMmodelcanbeadaptedtoconsumers,forinstanceby integratingtrustandrisk(Pavlou,2003),orcompatibility,privacy,security,normativebeliefs,and self-efficacy(Vijayasarathy,2004).Venkatesh,Thong,andXu(2012)proposeamodelofconsumer acceptanceoftechnologyderivedfromtheUTAUTmodel(Venkatesh,Morris,Davis&Davis., 2003).Thismodel,UTAUT2,considersperformanceexpectancy,effortexpectancy,socialinfluence, facilitatingconditions,hedonicmotivation,pricevalue,habit,age,genderandexperience.Individual characteristicsmoderatetheeffectofotherconstructsonbehaviouralintentionandtechnologyuse. Non-usershaveyettobecomeacorefocus.Somevariablesidentifiedinnon-useliterature,such astechnophobiaortechnologyanxietyareutilizedinconsumertechnologyresearchanddemonstrate animpactonconsumerperceptionself-servicetechnologies(Meuter,Ostrom,Bitner&Roundtree, 2003).Mobilizingnon-usecanbebeneficialtoascertainmoreunderstandingofconsumeracceptance andbehaviourwithtechnology. Thisanalysisofpriorliteratureshowsthat1)consumeruseoftechnologyhasbeenwell documented,butnon-usersandtheirperceptionofconsumermobileInternetservicesaremorescarcely discussed;2)thereisamethodologicaldifficultyimpliedbycapturingnon-useandcomparingitto formsofuse;3)theporositybetweenuseandnon-useappearsataconceptuallevelintheliterature, butempiricalevidencearestilllacking.Thisresearchproposestocaptureempiricallytheporosity betweenuseandnon-use.
RESEARCH QUESTIoN ANd METHodoLoGy Research Question Basedonthereviewofrelatedworks,wecanseethatthebinarybetweenusersandnon-usersdoesn’t seemtohold.Non-usersthemselvescanbecomesurrogateusersorreconsidertheirpositiongiven circumstances.Non-usagecanalsobepartialorstopped.Wearguethatthenecessityofdeveloping continuumofinvolvementwithtechnologiesholdsfornon-usersandusersalike,andthattheporosity ofuseandnon-useneedstoberesearchedmoreclosely.Thisporositymayberevealedbylookingat differentprojectedusesoftechnologies.That’swhyweconsidervariousaspectsofmobileInternet, astechnologyoverallbutalsothroughdifferentservicesalreadyavailabletoconsumerssuchasQR-code,augmentedreality,m-ticketandm-payment.Therefore,weformulatethefollowingquestions: RQ1:Whatarethecommonalitiesinoccasionaluser’s,heavyuser’s,andnon-user’spointsofview ontechnology? RQ2:WhathindersanddrivestheuseofservicessuchasQR-code,augmentedreality,m-ticketand m-payment?
A Brief Presentation of Q-Method
Understandingthemotivesbehindtechnologyuseandnon-userequiresauser-centredapproachthat canaccountforsubjectivereasons(not)tousetechnologies,inamultidimensionalmanner.More specifically,oneneedstodesignempiricalresearchdesignthata)overcomethedifficultiesthat non-usershavetoexplaintheirattitude,b)considerthatanindividual’spointofviewontechnology changesdependingonthespecificapplicationoftechnologyunderobservation,c)considerina holisticmannerthevarietyofvariablesbehinduseandnon-usedocumentedinpriorliterature. WechosetousetheQmethod(seeq-method.organdBrown,1993)asa)itallowstocapture thein-depthpointofviewofindividualsfromtheirownpointofviewbasedontherankingofgiven stimuli,b)toconsideramultitudeofvariablesincludedinthestimuli,andc)tothenidentifyshared viewsamongagivensamplethroughmathematicalanalysis.UsingQallowstoovercomethedual methodologicaldifficultypresentedbytheuseoftheporositybetweenindividuals’pointsofviewon useandnon-use.Q-methodhasbeenmobilizedinInformationSystemsabout15times(Gauzente, 2013),especiallytoexplainperceptionoftechnologybyindividuals.Yet,thedistinctionbetween usersandnon-usershasnotbeencentraltothesestudies. GiventhelackofpopularityofQ-methodinthefield,weprovideadescriptionofthekey conceptsbehinditandstepstoconductresearchwithQ.Q-methodwasdevelopedbythepsychologist Stephenson(1935;1953)tostudysubjectivity.Subjectivityisconceptualizedaswhat‘emanatesfroma particularvantagepoint’(Brown,1993).Fundamentally,Q-methodbelongstoqualitativeapproaches. Itpresentsaffinitywithphenomenology(Shinebourne&Adams,2007)andaimsatcapturingthe operantsubjectivityofindividualsinrelationtoanygiventopic,fromtheirownperspective. Qrestsontwoimportantpillars.Oneistheoreticalandreferstoconcoursetheory,theotheris methodologicalandusesQ-sortingprocedureandq-factorialanalysis(Gauzente;2010).Basedon theseelements,theproceduretofollowtosetupaQ-studyisasfollows: 1. ThefirststeptosetupaQ-studyistocreatetheconcourse.Concoursecanbedefinedasthe volumeofavailablestatementsonatopic.It‘isthecommoncoinageofsocietieslargeandsmall, andisdesignedtocovereverythingfromcommunitygossipandpublicopiniontotheesoteric discussionsofscientistsandphilosophers’(Brown,op.cit.).Evenforoneindividual,asingle wordcanhaveseveralmeanings,dependingoncircumstancesandtheindividual’smind-set. Whatisimportanttonoteisthatthesemeaningspartlyoverlapwithotherpeople’smeanings, andthisiswhatmakesinterpersonalcommunicationpossible.Basedontheseconsiderations,
Stephensonsuggeststhatinitialqualitativeinterviewsorliteraturereviewsshouldbeconductedto generateasmanymeaningsaspossibleconcerningonetopic.Thesemeaningscanbeformulated asstatements.Altogether,statementsconstitutetheq-sample; 2. Then,individualsareaskedtoproceedtoQ-sorting,i.erank-orderthestatementsaccordingto thedegreetowhichtheyrepresenttheirsubjectiveviewofonetopicinaforceddistribution matrix.Therespondentsaredesignatedasthep-sample.Thisrankingproceduredictatesthat onlyasmallportionofassertionswillbeselectedashighlyrepresentativeofone’spersonal vantagepoint,andonlyasmallportionwillbeselectedasbadlyrepresentative;themajoritywill beneitherrepresentativenornon-representative(seeTable1foradistributionof29statements). TheresultoftheQ-sortingprocessisaq-sort; 3. Factoranalysisisthenusedtoanalysethedata.Thisiscalledq-factoranalysisbecauseinstead ofanalysingindividuals,assertionsorstatementsareanalysed.Amapoftherepresentationsthat peoplehaveisproduced,whichhelpstoidentifythedifferentvisionsthatpeopleshare.Factor analysisisthususedtoidentifyunderlyingq-factorswhichcorrespondtosharedvisions.It shouldbeemphasizedthat,innoway,theq-factorsshouldbeassimilatedtogroupsofpeopleas intypologicalapproaches.Thefactorsarenotastatisticalrepresentationofgroupsinthegeneral population.Qfactorsaresharedviews,sharedinterpretationsofanobject. Qdoesnotaimatgeneralizationbutatcapturingexistingpointsofview.Therefore,itcan operatewithsmallsamples(McKeown&Thomas,2013).Stephenson(1974)hassuggestedsingle case-studiesasapromisingmethodologicalpossibilityinordertodevelopin-depthknowledgeof subjectiveissuesandtounveilanindividual’sinnerworld.Asheputsit,‘thenon-statisticalstrategy leadstoimmediateresults’(p.3,1974).Individualcasestudiesallowtoidentifythepointsofviewof anindividual,orbetteryetthemultitudeofpointsofviewonecanhaveonatopic.Tothisextent,the Researcheraimsatelicitingtherespondent’spointofviewfromdifferentperspectives,lookingatwhat therespondentthinksothersthinkaboutthetopic(Rhoads,2015)oraboutdifferentrepresentations ofthephenomena,i.edifferentformsoftechnologytoapprehendtheperceptionofmobileservices (Gauzente,2014).Thisresultsinonerespondentproceedingtoq-sortingseveraltimeswiththesame statementsbutchangingconditionsofinstructions.Thereisnostandardpertainingtothenumberof q-sortsneededfromonerespondenttoproceedwithasingle-case.Theresearchertakesintoaccount thenatureofthephenomenaunderstudy,thepossibilityfortherespondentstoanswer,thematerial generatedwiththerespondenttocreatetheconcourse,andthelevelofdepthandgranularitydeemed desirableforthestudy. Investigation Instrument Forthisstudy,thestatementswereselectedbasedonapriorQ-studylinkedtoAugmentedReality (Gauttier,Gauzente&Aikala,2016).TheResearchersaddedstatementsinordertocoverthe specificitiesofothermobiletechnologiesandimportantvariablesidentifiedintheliterature.For instance,theoriginalstatementsdidnotaddressthenotionofpaymentthroughmobileapplications, sotheResearchersbroughtthemin.Allinall,29statementswereselected.Theycoverthedifferent Table 1. Q-sort statements forced distribution
Absolutely Not Representative of My Point of View Don’t Agree or Disagree Absolutely Representative of My Point of View -3 -2 -1 0 1 2 3
theoreticaldimensionsidentifiedinbothresearchtraditions(InformationSystemsResearchand DigitalDivide/Non-Usagetradition). Nineconditionsofinstructionweregiven,resultingin9Q-sortsperrespondent(psample=3). Thenineconditionsentailtheparticipant’sa-prioriviewofdigitalmedia–asopposedtoprint-and hisa-posterioriviewoncethedifferenttechnologiesandserviceshavebeenpresentedandjudged. Thedifferenttechnologiesandserviceshavebeenchosenconsideringseveralaspects: • Thecurrentstateofmediatechnologies(m-ticket,QRcode); • Popularity:‘in-progress’mediatechnologiesthatbenefitedfrombuzzandthatmostpeopleare awareof(likegoogleglass,augmentedreality); • Thefunctionalityofmediatechnologies(m-ticket,m-payment); • Thefactthattechnologiesareclearlydocumentedonlinesothattheparticipantcanunderstand howitworks. Inordertogathermoresocialdimensions,wealsoincludetheviewofwhatfuturegenerations orparentsmightthink.Finally,nineconditionsofinstructionsareretained. Theconditionsofinstructionsareasfollows: 1. Whatisyourgeneralviewpointaboutavailablemobilemediatechnologies? 2. Aboutm-ticketforpublictransportation? 3. AboutQRcodeadvertising? 4. Aboutaugmented-realityproductpre-visualization? 5. AboutGoogleglass? 6. Aboutm-payments? 7. Nowthatwehaveseenseveralpossibilities,pleasereassessyourviewofmobileservices andtechnologies. 8. Inyouropinion,whatwouldbetheviewofyourparents? 9. Inyouropinion,whatwouldbetheviewoffuturegenerations? Foreachq-sortinstrument,anexampleofthemediatechnologywasfirstgiveneitherthrough picturesoronlinevideodemonstrationsinordertomakesurethattheparticipantsunderstoodwell themediatechnologyfeaturesandhadsimilarrepresentationsofthedifferenttechnologiesunder study.Itisnoteworthythat,asthestudywasdoneinFrance,thevideoswereshowingFrenchcases ofuseofthedifferenttechnologies.Allthesetechnologieswerewidelyavailableatthetimeofthe studyinFrance,withGoogleGlassesbeinganexception. Threepersonsparticipatedtothestudy,creatingatfirstthreesingle-casestudies,whichwere thenincludedtoformonedataset. ParticipantswereselectedbasedontheirreporteduseofmobileInternetandtechnologies.They wereaskedwhethertheyseethemselvesasheavy,occasionalornon-userduringthescreeningstage. Theirself-qualificationwasfurthercheckedwiththequestionnaireprecedingthefirstq-sort,inwhich participantswereaskedtocharacterizetheirrelationshiptotechnology,totheirmobilephones,and ratetheirattitudetomobiletechnologiesonascalefrom1(absolutelynegative)to5(absolutely positive).Thesampleconstitutesof: • Anon-userofmobileInternet,whodeclaresnothavingaccesstomobileInternetatallon herphoneandisnegativetowardstechnologiesoverall(2).Hernon-useofmobileInternetis voluntary.Therespondentwasnotabletocharacterizeherrelationshipfurtherpriortothestudy; • Anoccasionaluser,whodeclaresabouttechnologiesthat‘I just need a computer to check
web with other technologies, like my phone or my tablet, happens occasionally, like when I’m waiting or when I spend a couple of days out of home…’.Thisparticipantappearsasapartial
user,partialnon-user; • Aheavyuser,whodeclaresmobileInternetispartofhisdailylifeandhecould‘hardly do without it now’.Thisparticipant’susageofmobileInternetiswide,asmanyapplicationsarereported beingused,fromsocialnetworkstoonlinepurchases.Heishighlyfavorabletotechnology(4). AsummaryofparticipantcharacteristicsisprovidedinTable2. Theparticipantsproceededtotheq-sortsintheirdailyenvironment.TheResearchersexplained totheparticipantstheprocedureface-to-faceandwerepresentastheparticipantsdidthefirst q-sorting.Thisensuredthattheparticipantsunderstoodtheexerciseandcompleteditappropriately, sotheycouldfeelcomfortablewhenproceedingtotheremainingq-sorts.Theywereaskedto proceedto2q-sortsperweek,sothatdatacollectionlastedaround5weeks.Therewereseveral reasonsforthis.First,proceedingtoall9q-sortsoverashortperiodoftimewouldhavedecreased thequalityofthedatawegathered:participantswouldnothavehadtimetofullyconsidereach technologyonitsownandcouldhavebeentiredoftheexercise.Second,longdurationsofstudies areoftenabarrierforparticipants.5weeksappearedtobesufficientfortheResearchersandrather easytoacceptforparticipants. DuringthefirstQ-sortingprocedure,nocommentsweremadeonthestatements,suggesting thattheyweredeemedexhaustiveacrossthesample. Finally,q-factoranalysiswasrunonall27Q-sortsaltogether(3times9Q-sorts)onthePQ methodsoftware.Theresultsrevealfiveq-factors.Someofthemarerelativetooneuser,whilesome expresssharedviews.Table3summarizesthecharacteristicsofthesecond-orderfactors. RESULTS ThefiveviewsweobservefromthefivesyntheticQ-sortsaredescribedbelow.Thedescriptionof eachviewstemsfromthedataobtainedasaresultofthefactorialanalysis.Indeed,notonlydoes theanalysisidentifysharedviews,italsoprovidesthez-scoreofeachstatementforthatgivenview sothatitispossibletoseehowthepointofviewisstructuredandanalysetheroleofthedifferent Table 2. Participant characteristics
Non-User Occasional User Heavy User
Gender F F M
Age 32 26 35
Smartphone Yes Yes(2years) Yes(4years)
MobileInternet No Yes(Socialnetworks) Yes
Onlinepurchase No No Yes(upto300€) Attitudetomobile technologies(1= Absolutelynegative,5= absolutelypositive) 2 3 4
Roleofmobilephone Purelyfunctional PurelyFunctional Veryconvenient Relationshiptotechnology MobileInternetinspecificcircumstances–waiting
items.Then,theresearchershaveaccesstotablespresentingareasofdifferencesandconsensus acrossthefactors. Dataanalysisismadeintwosteps.Firstly,theresearchersanalyseonefactoraftertheother, lookingatitsstructure.Thestatementsz-scoreareusedtoproduceasyntheticq-sortfortheview. TheResearcherswriteasummaryforeachviewguidedbythestatementsthataremostagreedand disagreedwith.Secondly,theresearchersdoacomparativeanalysisofthefactorsbetweeneach otherusingthedataonareasofconsensusanddifferences.Thisallowstorevisethesummariesto makesurethatkeydistinguishingfactorsforeachsortarepresentinthedescription,increasingthe granularityoftheanalysis.Itallowstopresentacomparativesummary. Weprovideasummaryforeachfactorseparatelyandthenproposeacross-factorialdiscussion. Inthedescriptionsbelow,thenumbersinparenthesisafterthequotationsdenotetherankingofthe correspondingstatementinthesyntheticsortforeachview. Alldataconcerningthefivefactors,thesyntheticsorts,andthelistofstatementsusedinthis studycanbeaccesseduponrequesttotheauthors.
View 1: distanced View
Thefirstviewidentifiedisadistancedview.ItisdefinedbyseveralQ-sortsfromthenon-user (general,m-ticket,QRcode,augmentedreality,googleglasses,m-payment,ex-post)andexplains 25%ofvariance. Thispointofviewexpressesalackofinterestformobile,asournon-userisnot‘fondof’these technologies(+3)andshedoesn’twanttotrythem(+2).Technologiesarenotseenasdangerous (-2),buttheyarenotpleasanteither(-2),norexciting(-3).Thisviewshowsalackofanemotional connectiontomobiletechnologies.Itaddsuptoaperceivedlackoffunctionalityforthisparticular userastechnologiesare‘notvital,Idon’treallyneedit’,eventhoughtheyare‘coherentwithourmore andmoremobilewayoflife’(+2).Thereisideologicalreasonnottousetechnologies,nofearlinked tosecurityorprivacy,butalackofneedforthesemobiletechnologies.Thissuggestspeoplewith distancedviewssuchasthisnon-usermightcometousingtechnologiesdependingoncircumstances, whentheyhavearationalreasonforit.
View 2: Enthusiastic View
Thesecondviewidentifiedinthefactoranalysisisamoreenthusiasticview.Themostrepresentative Q-sortsdefiningthisviewaresomeoftheoccasionaluser(previsualisation,future),oftheheavy user(previsualisation,future)andofthenon-user(future).Itisinterestingtonotethatallrespondents sharesimilarrepresentationsoftechnologiesasseenbyfuturegenerations,andthatthispointof viewisapositiveone. Indeed,thispointofviewdepictstechnologiesasveryconvenientandpractical:theymakelife easier(+3)andallowtomakepurchasesfromanywhere(+3).Theyareseenasmodern(+2),and Table 3. Comparative Q-factors characteristics
2nd Order Q-Factor View #1 View #2 View #3 View #4 View #5
Involvedq-sort NUgeneral,NU m-ticket,NU QRcode,NU AR,NUGoogle glasses,NU M-payment,NU ex-post OU previsualisation, OUfuture,NU future,HU m-ticket,HU previsualisation, HUfuture OUparents,HU googleglass, HUm-payment, HUexpost,HU parents OUgeneral,OU googleglasses, HUQRcode OUm-payment %ofexplainedvariance (Total=79%) 25 18 17 11 8
onewould‘wanttotry’(+2).Inthisenthusiasticview,norealdangerislinkedtotechnology.One canunderstandhowtheywork.
View 3: Critical View
Thethirdviewisratherpessimistic,althoughitisdefinedmainlybyQ-sortsfromtheheavyuserof oursample(googleglasses,m-payment,ex-post,parents)andoneq-sortfromtheoccasionaluser (parents).Thisshowsthatuserscanbemorereluctanttowardsonetechnologythantheother,and beattimesnon-users. Thispointofviewhighlightsalackoftrustinmobiletechnologies,andafearonemightbecome dependentonthem(+3).Therearerisksassociatedtopaymentsecurity(+3).Technologyare dangerous(+2),andsynonymouswithadvertising(+2). Overall,peoplesharingthispointofviewarenotfondoftechnologies(+2).Thismightbe linkedtothelackofpositivehedonicexperienceperceivedbyparticipants:thisviewseesmobile technologiesasnotplayful,notexciting(-3),andnotpleasant(-3).
View 4: Need-Fulfilment Focused View
Thefourthviewuncoveredbytheanalysisisalsoacriticalone.ItisdefinedbyQ-sortsfrom theoccasionaluser(general,googleglasses)andtheheavyuser(QR-code).Inthisview,mobile technologiesimplyariskofdependency(+3)andarenotvital(+3).Peoplesharingthispointofview donotwanttotrytechnologiesandarenotfondofthem(+2),eventhoughtheyunderstandthem. Thispointofviewisrathernegative,butdoesn’tentailthedistrustanddangerseeninthethird view.Here,statementslike‘Thesetechnologiesaredangerous’arenegativelyrated(-2),whilethey appearedpositivelyratedinthepreviousview(+2).Themaindriverofthispointofviewseemsto bethelackofneedfortechnology.Itissomehowclosetoview1,exceptthatinview4participants claimtheyunderstandhowtechnologieswork,andareneutralwhenitcomestolinkingthemand lifestyle.Thisfourthpointofviewrepresentsanopiniononspecifictechnologies(QR-code,Google Glasses),whichappearasnotvitaltorespondents.Itisalsocomposedoftheq-sortontheoccasional user’sgeneralpointofviewoftechnologies.Theywouldbeoverallunnecessary,andyetusedin particularinstances.
View 5: Security-Centered View
Thelastpointofviewidentifiedisspecifictotheviewonm-paymentoftheoccasionaluserand expressessecurityconcerns.Thisviewistheonlyonecenteredaroundperceivedriskslinked todata-protectionandsecurityofpayment(+3).Itisseenasdangerous(+2)andgoodonlyto drawattention(+2). M-paymentisnotexciting(-3),notplayfulandtheuserexpressingthispointofviewwouldn’t tryitevenif[she]wouldn’thaveaminutetogotothestore.Rejectionisdrivenbyahighlevelof risksassociatedtotechnology.
Consensus and disagreement on Statements Among Points of Views
Eventhoughtheanalysisallowstoidentifydifferentpointsofviewandexplaineachofthem independently,italsoprovidesunderstandingintermsofconsensusanddifferencesacrosstheviews. Themostconsensualstatementsrefertothepossibilityfor‘brandsandcompaniestobecloserto consumers’,humancontact,questionslinkedtotariffsplanandmakinginformationmoreaccessible. Thesestatementsareallneutrallyrankedinall5views,indicatingthey’retakenforgranted. Somestatementsarealmosthomogenouslyrankedacrossviews.Itappearsthatallpointsofview shareanegativerankingof‘Thesetechnologiesareexciting!’(-3),‘Iamcurioustotry’(-2and-3), ‘pleasanttouse’(-2and-1),‘playfulandfun’(-1and-3)exceptforthesecond,enthusiasticview. Emotionalconnectionseemstobeoneofthemaindifferencebetweenenthusiasticperceptionof
technologies-whichwasformedmainlybyheavyuser’sQ-sorts,someoftheoccasionaluser,and onlythefuturelikerepresentationofthenon-user-andmoreprudentviews. Asfarastheutilitariandimensionisconcerned,oneshouldnotethatthecriticalview(view3) canbedistinguishedfromtheothersbytheneutralrankingof‘it’snotpractical’,whileallotherpoints ofviewshowanegativeattitudetothisstatement.Butperceivedutilityseemstobeexplainingmore thebehaviourappearinginrejectingandprudentviews,forwhich‘it’snotnecessary,Idon’tneedit’ ispositivelyrated(+3forview1and4;+1forviews3and5). Ideologydoesn’tseemtobedrivingnon-useanduse,asthestatementlinkedtohumanfactor andtheneedforfacetofaceinteractionappearedratherneutralamongallpointsofview,withthis statementrankedas0or+1.Besides,onlytheenthusiasticviewdisagreesthat‘it’sbettertogothe storethanlivebehindone’sscreen’(-2),whileinotherpointsofviewthisstatementisrated+1. Onlytheenthusiasticviewandtherejectingview(aroundthenon-user’sq-sort)arepositivethat technologiesare‘thefuture’,whileothersareneutral.Thispointsatthepossibilityforthenon-user toreconsiderherpositionatanotherpointintime. dISCUSSIoN Thefirstpurposeofthisstudywastoidentifywhethertherewerecommonalitiesbetweenthe pointsofviewofnon-user,occasionaluserandheavyuseronmobiletechnologies.Bylookingat thephenomenaofuseandnon-usefromauser’sperspectiveandcapturingdifferentdimensionsof attitudetowardstechnology,thisstudyshowsthattheboundarybetweenheavyuser,occasionaluser andnon-userisporous. Indeed,withtheexceptionofviews1and5,allviewsinoursampleareconstitutedbyQ-sorts fromtwotothreetypesofusers.Theanalysisofconsensualstatementsamongviewsalsoshows thatvariablescanberatedthesame,implyingthatthethreeuserssharethesamepointofviewon suchconstructsasaccesstoinformation,accesstotechnologyandtariffplans,ortheneedforhuman contact.Someotherconstructsarenothomogenousacrossallpointsofviews,butalmost.Theyrefer tothesharedmeaningoftheoccasionalandheavyuser,non-userandheavy-user,andnon-userand occasionaluser. Porosityalsoworksintermsoftheidentityandbehaviourdisplayedbyusersandnon-users.As indicatedinNevesetal(2015),non-userscanbeseenaspotentialconverts.Inourstudy,thenon-user’sviewoffutureandtechnologyisasenthusiasticastheoneoftheheavyusertoday,whichmay indicateapossiblereconsiderationofattitudewithtime. Whenconsideringparticulartechnologies,onecanseethattheheavyuserisclosetotheoccasional user’sviews(ofothertechnologies),asitisthecasefortheheavyuser’ssortonQRcode,whichcreates view4togetherwiththeoccasionaluser’sgeneralq-sortandq-sortongoogleglasses.Thepointof viewoftheheavyuserappearsinthreeviews,drawingonsortsondifferenttechnologies,indicating amulti-dimensionalrelationshiptotechnologywithinthisuser,anddifferentdegreesofcloseness toothertypesofusers.Thedegreeofinvolvementmustbelookedatfordifferentapplicationsofa technology,asheremobileInternetwasillustratedwith5specificexamplesofuse.Furthermore, thenon-user’srejectingpointofviewdescribedinview1appearstobedrivenmorebyalackof perceivedutilityforhercircumstancesthananideologicalresistance,suggestingpossibilitiesfor acceptanceofmobiletechnologiesindifferentcircumstances.Thereisanegotiation,somebricolage andassemblagebetweenideologicalmotives(riskofdependency),security-andprivacy-relatedrisks tobetaken,conveniencetobegained,inallsituations. Therefore,theideaoflookingatuseandnon-useasatcontinuumofengagementwithtechnology (Wyatt,2014)seemsvalid,pushingtowardsaporositymodeloftechnologyacceptance.Ourstudy allowstodocumentmotivationsbehindnon-use,partialnon-use,partialuseanduse(seeFigure1). Non-use,voluntaryornot,istheabsenceoftechnologyusage.Thefirstviewidentifiedinthis studycorrespondstothenon-user’sQ-sortsandshowslackofinterestfortechnology,explaining
voluntarynon-use.Thefifthview,basedontheoccasionaluser’sq-sortonm-paymentshows rejectionoftechnologyforsecurityconcerns,andcanbeattachedtonon-use.Itisinlinewiththe self-declarednon-useofm-paymentbytheparticipant.Partialnon-usedescribestheintentionalnon-useofatechnologyinspecificsettingorperiodoftime.Itstemsfromareflexive,criticalapproach. Thisapproachwasidentifiedinview3,basedonsomeoftheheavyuser’sandoccasionalusers’ Q-sorts,andshowsthatriskslinkedtotechnologyusecanovercometheotherwisepositiveattitude ofparticipantstotechnology.Perceivedriskscanleadtopartialnon-useoftechnology,orvoluntary non-use.Partialuseischaracterizedbytheuseofatechnologyinaspecificsettingorperiodof time,whichcorrespondstotheoccasionaluserofourstudy,whousesmobileinternettechnologies inspecificcircumstancessuchasbeingawayforacoupleofdaysorwaitingsomewhere.Partial usecanbedrivenbytheneedtofulfilconcreteneeds,asidentifiedinview4.Usereferstoviews acceptingtechnology,andinwhichonewantstotryit.Inthisstudy,itisvisibleinview2,whichis structuredaroundpositiveperceptionofbothfunctionalandhedonicaspectsoftechnology.Notions offrequencyofusecouldbedocumentedinfurtherresearch(dailyuse,moderateuse,etc).Inthis study,theywereself-declaredandbasedongeneraluseoftechnology,notofspecificservices.That levelofgranularitycouldbedocumentedinfurtherresearch,soastohighlightmotivesforprolonged useandloyaltytotechnologyconsumerservices. Besideshighlightingtheartificialityofthebinaryuse/non-use,thisstudyprovidesinsightsin termsofvariablesexplaininguseandnon-useandshowshownewmethodcanhelpdocumentthe phenomenon.Thisstudyconfirmstherelevanceofcertainconstructsinexplainingtechnologyuse andnon-use,suchasthehedonicaspect(Venkateshetal.,2012;Beaudry&Pinsonneau,2005,2010), whichappearedstronglyinallviewssomewhatacceptingtechnologies.Thenotionofcontextand facilitatingconditions(Venkateshetal.,2012;Goodhue&Thompson,1995)isalsostructuringviews, asthenon-userseemsnottoidentifymomentsortaskstechnologycouldhelpherwith(view4). Second,fromamanagerialstandpoint,thisstudyspeakstothemotivationsbehinduse/non-use, whichcanbeutilizedtosupportconversionofpotentialusers.Indeed,lookingatthecontinuum obtained(Figure1),onecanseehowparticipantsareboth(partial)non-usersand(partialusers).This meansthatbyaddressingsecurityissues(view5)andhighlightingfunctionalaspectsoftechnology (view4),thepenetrationofconsumertechnologyusagecouldbeincreased.Theresultsofthis studyalsoshowthatnotallconsumermobileservicesareperceivedinthesamewayastheypresent Figure 1. A continuum of non-use and use, illustrated with the 3 cases presented in this study: A porosity model of use / non-use
differentprosandconsfordifferenttypesofusers.M-paymentappearsinthreedifferentviews(1;3 and5),whicharerejectingorambivalentviews,wherenon-useisdrivenbycriticalconsiderationsor securityconcerns.Thisperceptionisfarfromtheenthusiasticviewofusersonprevisualisation,future technologiesorevenm-ticket,whichisdrivenbybothhedonicmotivationandfunctionalrelevance.To spreadthistechnology,securityconcernsmustbeaddressed,anditmustbemadecleartoconsumers howthistechnologycanhelpthem(echoingview4,butalsoview1inwhichthenon-userdoesn’t feeltheneedforthesetechnologies).Thewow-effectoftenassociatedwithnewtechnologydoesn’t appearasadriveronthecontinuumofuseandnon-use.Thisalsomeansthatwhenpreparingthe launchofnewconsumertechnologies,marketersshouldinvolvenotonlypeoplewhoaregenerally favourabletotechnology,butalsoindividualspresentingmoreprudentprofiles.Thiswouldallowto identifyscenariosofuse,barriers,anddesigncommunicationsaddressingthem,soastoguarantee ahigherpenetrationratefortheserviceslaunched. Finally,Qisusedtotacklechallengesidentifiedbyliterature.Previousworkpointstothedifficulty ofnon-usersexplainingtheirbehaviourbeyondadeclarationofuseandnon-use(VanHouse,2015). Approachesinvolvingdatatriangulationarerequired,aswellasapproachesthatallowparticipants toexpresstheirpointsofviewbyreactingtospecificstimuli.Besides,researchonnon-usersfocuses onpracticesofnon-use(Ems,2015),butthemotivationsbehindnon-usearenotexplainedmuch. Q-methodprovidedatoolforthenon-usertobeabletoexpressherpointofviewinanarticulated waysoastoidentifyoperantfactors,thatguideparticipants’behaviours.TheuseofQalsoallowed tocomparethepointsofviewofdifferentusersinastructuredwaysothatqualitativecomparative analysiscouldbecarried.Furtherdevelopmentscouldattemptatmeasuringthedifferentvariables atstakeandoffercomparativeanalysisonlargersamples.Thelatterwouldallowtoweightinthe roleofgender,habitsandotherindividualcharacteristicsthathavebeenidentifiedasmoderating theimpactofhedonicandfunctionalvariables.Splittingusersintopartialusers,moderateusersand intensiveuserscouldallowtogainamorenuancedunderstandingofmotivationsbehinduseaswell. CoNCLUSIoN Usersandnon-usersofconsumermobileservicessharecommonrepresentations.Theycanallbe criticalattimes;whentheyarenotsureofthefunctionalroleoftheserviceconsidered,orwhen otherstructuralissuesareatstake(privacy,dataprotection).Theycanalsobeenthusiasticabout technologiesastheyarenoworhowtheywillbeinthefuture,highlightingbothgrowingdemands towardstechnologyandapotentialincreaseinusersoftheseservices.Theirpointsofviewaredefined inrelationshiptospecifictechnologies.Andeventhenon-user’srejectingpointofviewshowsthere isroomforchangeifonlytechnologycouldfillinaneed.Lookingatthecontinuumofusersand non-usersisthusrelevantgiventheporositybetweenthetwogroups,especiallywhendesigningnew technologiesandevaluatingthem.Indeed,byunderstandingsharedrepresentations,onecandesign andcommunicatenewtechnologiesinawaytoconvertnon-usersinpotentialusers.
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ENdNoTES
Stéphanie Gauttier (stephanie.gauttier@etu.univ-nantes.fr) is a PhD candidate at the University of Nantes, France, and a Marie Curie Fellow at Trinity College Dublin, Ireland. Her research focuses on consumer perception and use of new technologies such as augmented reality.
Claire Gauzente (Claire.gauzente@univ-nantes.fr) is Professor in Management & Social Sciences at the University of Nantes, France, and Adjunct Director of LEMNA Research Lab. Her research interests encompass perception and use of ICT.
